Machine-Learning Methods for Complex Flows

被引：1
|
作者：
Vinuesa, Ricardo [1 ]
Le Clainche, Soledad [2 ]
机构：
[1] KTH Royal Inst Technol, Engn Mech, FLOW, S-11428 Stockholm, Sweden
[2] Univ Politecn Madrid, Sch Aerosp Engn, Madrid 28040, Spain
来源：
ENERGIES | 2022年 / 15卷 / 04期
基金：
瑞典研究理事会;
关键词：
MODELS;
D O I：
10.3390/en15041513
中图分类号：
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号：
0807 ; 0820 ;
摘要：
38
引用
收藏
页数：5
相关论文
共 50 条
  • [1] Methods for Automatic Machine-Learning Workflow Analysis
    Wendlinger, Lorenz
    Berndl, Emanuel
    Granitzer, Michael
    MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES, ECML PKDD 2021: APPLIED DATA SCIENCE TRACK, PT V, 2021, 12979 : 52 - 67
  • [2] Machine-Learning Methods on Noisy and Sparse Data
    Poulinakis, Konstantinos
    Drikakis, Dimitris
    Kokkinakis, Ioannis W.
    Spottswood, Stephen Michael
    MATHEMATICS, 2023, 11 (01)
  • [3] Machine-Learning Methods for Computational Science and Engineering
    Frank, Michael
    Drikakis, Dimitris
    Charissis, Vassilis
    COMPUTATION, 2020, 8 (01)
  • [4] How can machine-learning methods assist in virtual screening for hyperuricemia? A healthcare machine-learning approach
    Ichikawa, Daisuke
    Saito, Toki
    Ujita, Waka
    Oyama, Hiroshi
    JOURNAL OF BIOMEDICAL INFORMATICS, 2016, 64 : 20 - 24
  • [5] Travelling through levels of resolution with machine-learning methods
    Lemke, Tobias
    Hunkler, Simon
    Kukharenko, Oleksandra
    Peter, Christine
    ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, 2019, 257
  • [6] Review of Medical Decision Support and Machine-Learning Methods
    Awaysheh, Abdullah
    Wilcke, Jeffrey
    Elvinger, Francois
    Rees, Loren
    Fan, Weiguo
    Zimmerman, Kurt L.
    VETERINARY PATHOLOGY, 2019, 56 (04) : 512 - 525
  • [7] MEMS Accelerometers Classification Using Machine-Learning Methods
    Nevlydov, Igor
    Ponomaryova, Ganna
    Miliutina, Svitlana
    Bortnikova, Viktoriia
    2017 XIIITH INTERNATIONAL CONFERENCE ON PERSPECTIVE TECHNOLOGIES AND METHODS IN MEMS DESIGN (MEMSTECH), 2017, : 51 - 55
  • [8] Machine-learning approaches in drug discovery: methods and applications
    Lavecchia, Antonio
    DRUG DISCOVERY TODAY, 2015, 20 (03) : 318 - 331
  • [9] Prediction of Hemolytic Toxicity for Saponins by Machine-Learning Methods
    Zheng, Suqing
    Wang, Yibing
    Liu, Hongmei
    Chang, Wenping
    Xu, Yong
    Lin, Fu
    CHEMICAL RESEARCH IN TOXICOLOGY, 2019, 32 (06) : 1014 - 1026
  • [10] An evaluation of machine-learning methods for predicting pneumonia mortality
    Cooper, GF
    Aliferis, CF
    Ambrosino, R
    Aronis, J
    Buchanan, BG
    Caruana, R
    Fine, MJ
    Glymour, C
    Gordon, G
    Hanusa, BH
    Janosky, JE
    Meek, C
    Mitchell, T
    Richardson, T
    Spirtes, P
    ARTIFICIAL INTELLIGENCE IN MEDICINE, 1997, 9 (02) : 107 - 138
12345